Evaluating Multiple Arthropod Taxa as Indicators of Invertebrate Diversity in Old Fields

Biodiversity, often quantified by species richness, is commonly used to evaluate and monitor the health of ecosystems and as a tool for conservation planning. The use of one or more focal taxa as surrogates or indicators of larger taxonomic diversity can greatly expedite the process of biodiversity measurement. This is especially true when studying diverse and abundant invertebrate fauna. Before indicator taxa are employed, however, research into their suitability as indicators of greater taxonomic diversity in an area is needed. We sampled invertebrate diversity in old fields in southern Michigan using pitfall trapping and morphospecies designations after identification to order or family. Correlation analysis was used to assess species richness relationships between focal arthropod taxa and general invertebrate diversity. Relationships were assessed at two fine spatial scales: within sampling patches, and locally across four sampling patches. Cumulative richness of all assessed taxa increased proportionately with cumulative invertebrate richness as sampling intensity increased within patches. At the among-patch scale, we tentatively identified Hemiptera and Coleoptera as effective indicator taxa of greater invertebrate richness. Although Hymenoptera, Araneae and Diptera exhibited high species richness, their total richness within patches was not associated with overall invertebrate richness among patches. Increased sampling throughout the active season and across a greater number of habitat patches should be conducted before adopting Hemiptera and Coleoptera as definitive indicators of general invertebrate richness in the Great Lakes region. Multiple sampling techniques, in addition to pitfall trapping, should also be added to overcome capture biases associated with each technique

The contribution of North Atlantic atmospheric circulation shifts to future wind speed projections for wind power over Europe

Wind power accounts for a large portion of the European energy mix (~17% of total power capacity). European power systems therefore have a significant - and growing - exposure to near-surface wind speed changes. Despite this, future changes in European wind climate remain relatively poorly studied (compared to, e.g., temperature or precipitation), and there is limited understanding of the differences shown by different general and regional circulation models (GCMs and RCMs). This study provides a step towards a process-based understanding of European wind speed changes by isolating the component associated with `large-scale' atmospheric circulation changes in the CMIP5 simulations. The component associated with the large-scale atmospheric circulation is found to explain cold season windiness projections in the free troposphere over Western Europe, with the changes reflecting the poleward shift of the North Atlantic jet. However, in most GCMs the projected wind speed changes near the surface are more negative than would be expected from the large-scale circulation alone. Thus, while the spread in CMIP5 21st century near surface wind speed projections is associated with divergent projections for the large-scale atmospheric circulation, there is a remarkably good agreement concerning a relative reduction in near-surface wind speeds. This analysis suggests that projected 21st century wind speed changes over Western Europe are the result of two distinct processes. The first is associated with changes in the large-scale atmospheric circulation, while the second is likely to be more local in its connection to the near-surface boundary layer. An improved process-based understanding of both is needed for enhancing confidence in wind-power projections on multi-decadal timescales

How do owner managed businesses transform into ambidextrous organisations?

Organisational ambidexterity research has traditionally focused on large firms. This research answers the call for longitudinal studies into how smaller owner managed businesses balance exploration and exploitation to transform themselves into an ambidextrous organisation. They have different characteristics such as resource availability, informal organisational structure and direct owner manager control, often with nebulous strategic orientation. Empirical research has tended to examine these specific categories and frameworks in isolation observing past behaviour or testing hypotheses. This thesis takes a more holistic, dynamic and open approach via an action research case study that links three established ambidexterity frameworks to the practical implementation of predetermined interventions. This study benefits from the rare opportunity of the researcher also being operationally embedded, leading the design of the controlled action research interventions from theoretical frameworks. It observes a companywide transition to ambidexterity experiencing the dynamic impact of turbulence and complexity from pre-commencement analysis, initiation, conceptualisation, implementation and monitoring, over a three year time horizon. This enabled real time, data rich findings and critical reflective analysis, which contrasts with the usual case study approach of observing past events outside of the researcher’s control trying to match actual events to theory. The research is supplemented by data from independent interviews of other owner managed businesses to verify and triangulate findings. The resultant contribution is the design of a practical ambidexterity toolkit template combining for the first time three established theoretical frameworks. This toolkit presents a new practical five stage ambidexterity pathway supported by sixteen questions developed from practical findings. The first stage is a pre-commencement stage, ensuring a strategy exists which is aligned to ambidexterity. The second stage helps choose the appropriate initiation charter. The third stage conceptualises a plan tailored to a firm’s unique characteristics before implementing this plan as the fourth stage. The fifth monitoring stage acknowledges the dynamic longitudinal aspects and how to measure and monitor progress over the implementation time horizon to efficiently optimise exploration and exploitation balance. The five stage process allows a practitioner to take this standardised toolkit template and tailor it via sixteen questions to design a bespoke ambidextrous pathway, grounded in theory, acknowledging a firm’s unique characteristics and one size does not fit all

Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead-times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms and technical barriers frequently prohibit use by non-meteorological specialists. This paper therefore presents data produced through a new EU climate services program Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data corresponds to a suite of well-documented, easy-to-use, self-consistent daily- and nationally aggregated time-series for wind power, solar power and electricity demand across 28 European countries. The data is accessible from http://dx.doi.org/10.17864/1947.275, (Gonzalez et al., 2020). The data includes a set of daily ensemble reforecasts from two leading forecast systems spanning 20-years (ECMWF, an 11 member ensemble, with twice weekly starts for 1996-2016, totalling 21,210 forecasts) and 11 years (NCEP, a 12 member lagged-ensemble, constructed to match the start dates from the ECMWF forecast. from 1999-2010, totalling 4608 forecasts). The reforecasts containing multiple plausible realisations of daily-weather and power data for up to 6 weeks in the future. To the authors’ knowledge, this is the first time fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead-times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy- and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this

The structural history and mineralization controls of the world-class Geita Hill gold deposit, Geita Greenstone Belt, Tanzania

The Geita Hill gold deposit is located in the Archean Geita Greenstone Belt and is one of the largest gold deposits in East Africa. The Geita Greenstone Belt experienced a complex deformation and intrusive history that is well illustrated and preserved in and around the Geita Hill gold deposit. Deformation involved early stages of ductile shearing and folding (D1 to D5), during which episodic emplacement of large diorite intrusive complexes, sills, and dykes occurred. These ductile deformation phases were followed by the development of brittle-ductile shear zones and faults (D6 to D8). The last stages of deformation were accompanied by voluminous felsic magmatism involving the intrusion of felsic porphyry dykes, within the greenstone belt, and the emplacement of large granitic bodies now forming the margins of the greenstone belt. Early, folded lamprophyre dykes, and later lamprophyre dykes, crosscutting the folded sequence are common, although volumetrically insignificant. The gold deposit formed late during the tectonic history of the greenstone belt, post-dating ductile deformation and synchronous with the development of brittle-ductile shear zones that overprinted earlier structural elements. The main mineralizing process involved sulfide replacement of magnetite-rich layers in ironstone and locally the replacement of ferromagnesian phases and magnetite in the diorite intrusions. The intersection between the brittle-ductile (D6) Geita Hill Shear Zone and different structural elements of ductile origin (e.g., fold hinges), and the contact between banded ironstone and folded diorite dykes and sills provided the optimal sites for gold mineralization

A new approach to extended-range multi-model forecasting: sequential learning algorithms

Multi-model combinations are a well established methodology in weather and climate prediction and their benefits have been widely discussed in the literature. Typical approaches involve combining the output of different numerical weather prediction (NWP) models using constant weighting factors, either uniformly distributed or determined through a prior skill assessment. This strategy, however, can lead to sub-optimal levels of skill as the performance of NWP models can vary with time (e.g., seasonally varying skill, changes in the forecasting system). Moreover, standard combination methods are not designed to incorporate predictions derived from sources other than NWP systems (e.g., climatological or time-series forecasts). New algorithms developed within the Machine Learning community provide the opportunity for `online prediction’ (also referred to as `sequential learning’). These methods consider a set of weighted predictors or `experts’ to produce subsequent predictions in which the combination or `mixture’ is updated at each step to optimize a loss or skill function. The predictors are highly flexible and can transparently combine both NWP- and statistically- derived forecasts. A set of these online prediction methods are tested and compared to standard multi-model combination techniques to assess their usefulness. The methods are general and can be applied to any model-derived predictand. A set of weather-sensitive European country-aggregate energy variables (electricity demand and wind power) are selected for demonstration purposes. Results show that these innovative methods exhibit significant skill improvements (i.e., between 5\% and 15\% improvement in the probabilistic skill) with respect to standard multi-model combination techniques for lead weeks up to 5. The incorporation of statistically-derived predictors (based on historical climate data) alongside NWP forecasts are also shown to contribute significant skill improvements in many cases

Response of the North Atlantic storm track to climate change shaped by ocean–atmosphere coupling

A poleward shift of the mid-latitude storm tracks in response to anthropogenic greenhouse-gas forcing has been diagnosed in climate model simulations1, 2. Explanations of this effect have focused on atmospheric dynamics3, 4, 5, 6, 7. However, in contrast to storm tracks in other regions, the North Atlantic storm track responds by strengthening and extending farther east, in particular on its southern flank8. These adjustments are associated with an intensification and extension of the eddy-driven jet towards western Europe9 and are expected to have considerable societal impacts related to a rise in storminess in Europe10, 11, 12. Here, we apply a regression analysis to an ensemble of coupled climate model simulations to show that the coupling between ocean and atmosphere shapes the distinct storm-track response to greenhouse-gas forcing in the North Atlantic region. In the ensemble of simulations we analyse, at least half of the differences between the storm-track responses of different models are associated with uncertainties in ocean circulation changes. We compare the fully coupled simulations with both the associated slab model simulations and an ocean-forced experiment with one climate model to establish causality. We conclude that uncertainties in the response of the North Atlantic storm track to anthropogenic emissions could be reduced through tighter constraints on the future ocean circulation

A flexible approach to introductory programming : engaging and motivating students

© 2019 Copyright is held by the owner/author(s). In this paper, we consider an approach to supporting students of Computer Science as they embark upon their university studies. The transition to Computer Science can be challenging for students, and equally challenging for those teaching them. Issues that are unusual – if not unique – to teaching computing at this level include • the wide variety in students background, varying from no prior experience to extensive development practice; • the positives and negatives of dealing with self-taught hobbyists who may developed buggy mental models of the task in hand and are not aware of the problem; • the challenge of getting students to engage with material that includes extensive practical element; • the atypical profile of a computing cohort, with typically 80%+ male students. The variation in background includes the style of prior academic experience, with some students coming from traditional level 3 (i.e. A-levels), some through more vocational routes (e.g. B-Tech, though these have changed in recent years), through to those from experiential (work based) learning. Technical background varies from science, mathematical and computing experience, to no direct advanced technical or scientific experience. A further issue is students’ attainment and progression within higher education, where the success and outcomes in computer science has been identified as particularly problematic. Computer Science has one the worst records for retention (i.e. students leaving with no award, or a lower award than that originally applied for), and the second worst for attainment (i.e. achieving a good degree, that being defined as a first or a 2:1). One way to attempt to improve these outcomes is by identifying effective ways to improve student engagement. This can be through appropriate motivators – though then the balance of extrinsic versus intrinsic motivation becomes critical. In this paper, we consider how to utilize assessment – combining the formative and summative aspects - as a substitute for coarser approaches based on attendance monitoring

A flexible approach to introductory programming : engaging and motivating students

© 2019 Copyright is held by the owner/author(s). In this paper, we consider an approach to supporting students of Computer Science as they embark upon their university studies. The transition to Computer Science can be challenging for students, and equally challenging for those teaching them. Issues that are unusual – if not unique – to teaching computing at this level include • the wide variety in students background, varying from no prior experience to extensive development practice; • the positives and negatives of dealing with self-taught hobbyists who may developed buggy mental models of the task in hand and are not aware of the problem; • the challenge of getting students to engage with material that includes extensive practical element; • the atypical profile of a computing cohort, with typically 80%+ male students. The variation in background includes the style of prior academic experience, with some students coming from traditional level 3 (i.e. A-levels), some through more vocational routes (e.g. B-Tech, though these have changed in recent years), through to those from experiential (work based) learning. Technical background varies from science, mathematical and computing experience, to no direct advanced technical or scientific experience. A further issue is students’ attainment and progression within higher education, where the success and outcomes in computer science has been identified as particularly problematic. Computer Science has one the worst records for retention (i.e. students leaving with no award, or a lower award than that originally applied for), and the second worst for attainment (i.e. achieving a good degree, that being defined as a first or a 2:1). One way to attempt to improve these outcomes is by identifying effective ways to improve student engagement. This can be through appropriate motivators – though then the balance of extrinsic versus intrinsic motivation becomes critical. In this paper, we consider how to utilize assessment – combining the formative and summative aspects - as a substitute for coarser approaches based on attendance monitoring

The impact of monsoon intraseasonal variability on renewable power generation in India

India is increasingly investing in renewable technology to meet rising energy demands, with hydropower and other renewables comprising one-third of current installed capacity. Installed wind-power is projected to increase 5-fold by 2035 (to nearly 100GW) under the International Energy Agency’s New Policies scenario. However, renewable electricity generation is dependent upon the prevailing meteorology, which is strongly influenced by monsoon variability. Prosperity and widespread electrification are increasing the demand for air conditioning, especially during the warm summer. This study uses multi-decadal observations and meteorological reanalysis data to assess the impact of intraseasonal monsoon variability on the balance of electricity supply from wind-power and temperature-related demand in India. Active monsoon phases are characterised by vigorous convection and heavy rainfall over central India. This results in lower temperatures giving lower cooling energy demand, while strong westerly winds yield high wind-power output. In contrast, monsoon breaks are characterised by suppressed precipitation, with higher temperatures and hence greater demand for cooling, and lower wind-power output across much of India. The opposing relationship between wind-power supply and cooling demand during active phases (low demand, high supply) and breaks (high demand, low supply) suggests that monsoon variability will tend to exacerbate fluctuations in the so-called demand-net-wind (i.e., electrical demand that must be supplied from non-wind sources). This study may have important implications for the design of power systems and for investment decisions in conventional schedulable generation facilities (such as coal and gas) that are used to maintain the supply/demand balance. In particular, if it is assumed (as is common) that the generated wind-power operates as a price-taker (i.e., wind farm operators always wish to sell their power, irrespective of price) then investors in conventional facilities will face additional weather-volatility through the monsoonal impact on the length and frequency of production periods (i.e. their load-duration curves)